R Notebook

This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.

Try executing this chunk by clicking the Run button within the chunk or by placing your cursor inside it and pressing Cmd+Shift+Enter.

library(plotly)

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

Add a new chunk by clicking the Insert Chunk button on the toolbar or by pressing Cmd+Option+I.

When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the Preview button or press Cmd+Shift+K to preview the HTML file).

The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike Knit, Preview does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.

names(df)

 [1] "Release"               "Release.date"          "Release.type"          "Band"                  "Genre"                
 [6] "Location"              "Lyrical.themes"        "Number.of.reviews"     "Average.rating"        "genre_early"          
[11] "genre_later"           "genre_early_secondary" "genre_later_secondary" "location_early"        "genre_early_main"     
[16] "genre_later_main"      "genre_early_stripped"  "genre_later_stripped" 

df <-  filter(!(genre_early_main %in% c('Rock', 'Other'))) %>% 
  mutate(release_year = as.numeric(str_sub(Release.date,1,4)))

Error in genre_early_main %in% c("Rock", "Other") : 
  object 'genre_early_main' not found

levels(df_year$genre_early_main)

 [1] "Heavy Metal"       "Doom Metal"        "Thrash Metal"      "Power Metal"       "Nu Metal"          "Progressive Metal"
 [7] "Black Metal"       "Metalcore"         "Death Metal"       "Folk Metal"        "Ambient"          

g1 <- ggplot(df_year, aes(x=release_year, y=percent, fill=fct_rev(genre_early_main))) + 
    geom_area(position = 'stack') + 
  labs(x="Release Year", 
       y = "Percent of Releases", 
       fill = "Main Genre",
       title = "Percent of Metal Genre Releases By Year") + 
  #xlim(c(1970, 2018)) + ylim(c(0, 1)) + 
    scale_y_continuous(limits=c(0,1), labels = scales::percent, expand = c(0, 0)) + 
  scale_x_continuous(limits=c(1970, 2018), expand = c(0, 0)) + 
  scale_fill_manual(values = c("Black Metal" = "#000000", #black
                                "Death Metal" = "#8f0000", #dark red
                               "Thrash Metal" = "#7cf000", #light green
                               "Doom Metal" = "#7e3f0c", #brown
                               "Ambient" = "#7d7d7d", #gray
                               "Power Metal" = "#f72bad", #pink
                               "Heavy Metal" = "#1d00fa", #blue
                               "Metalcore" = "#ee6917",
                               "Nu Metal" = "#ffd60a",
                               "Progressive Metal" = "#0adeff", #light blue
                               "Folk Metal" = "#b120d9" #purple
                               )
                     ) + 
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
  panel.background = element_blank(), axis.line = element_line(colour = "black"))
ggplotly(g1)

names(df)

 [1] "Release"               "Release.date"          "Release.type"          "Band"                  "Genre"                
 [6] "Location"              "Lyrical.themes"        "Number.of.reviews"     "Average.rating"        "genre_early"          
[11] "genre_later"           "genre_early_secondary" "genre_later_secondary" "location_early"        "genre_early_main"     
[16] "genre_later_main"      "genre_early_stripped"  "genre_later_stripped"  "release_year"         

g2 <- df %>% filter(!(genre_early_main %in% c('Rock', 'Other'))) %>%
  mutate(release_year = as.numeric(str_sub(Release.date, 1, 4)),
         Average.rating = round(Average.rating, 1)) %>% 
  filter(Number.of.reviews >= 5) %>%
  ggplot() + 
  geom_point(aes(x = Number.of.reviews, 
                 y = Average.rating,
                 color = genre_early_main,
                 text=sprintf("Band: %s
                              Release: %s
                              Release Date: %s
                              Genre: %s
                              Rating: %s
                              Number of Reviews: %s
                              Tags: %s", 
                              Band, Release, Release.date, genre_early_main, Average.rating, Number.of.reviews, genre_early_stripped)), 
             position = position_jitter(width = 0.5, height = 0.5),
             size = 0.4,
             alpha = 0.6
             ) + 
  labs(x="Number of Reviews", 
       y = "Rating", 
       color = "Main Genre",
       title = "Metal Releases By Rating and Number of Reviews") + 
    scale_color_manual(values = c("Black Metal" = "#000000", #black
                                "Death Metal" = "#8f0000", #dark red
                               "Thrash Metal" = "#7cf000", #light green
                               "Doom Metal" = "#7e3f0c", #brown
                               "Ambient" = "#7d7d7d", #gray
                               "Power Metal" = "#f72bad", #pink
                               "Heavy Metal" = "#1d00fa", #blue
                               "Metalcore" = "#ee6917",
                               "Nu Metal" = "#ffd60a",
                               "Progressive Metal" = "#0adeff", #light blue
                               "Folk Metal" = "#b120d9" #purple
                               )
                     ) + 
    scale_y_continuous(limits=c(0,100),  expand = c(0, 0)) + 
  scale_x_continuous(limits=c(5, 45), expand = c(0, 0)) + 
  theme_light() + 
  theme(#panel.grid.major = element_blank(), 
        #panel.grid.minor = element_blank(),
        #panel.background = element_blank(), 
        axis.line = element_line(colour = "black"))

Ignoring unknown aesthetics: text

  #geom_jitter()
ggplotly(g2, tooltip="text")

df %>% plot_ly(x = ~Number.of.reviews, y = ~Average.rating, name = "Band")

No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode